NDLI: Retrieving answers from frequently asked questions pages on the web

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Retrieving answers from frequently asked questions pages on the web

Content Provider	ACM Digital Library
Author	Jijkoun, Valentin de Rijke, Maarten
Abstract	We address the task of answering natural language questions by using the large number of Frequently Asked Questions (FAQ) pages available on the web. The task involves three steps: (1) fetching FAQ pages from the web; (2) automatic extraction of question/answer (Q/A) pairs from the collected pages; and (3) answering users' questions by retrieving appropriate Q/A pairs. We discuss our solutions for each of the three tasks, and give detailed evaluation results on a collected corpus of about 3.6Gb of text data (293K pages, 2.8M Q/A pairs), with real users' questions sampled from a web search engine log. Specifically, we propose simple but effective methods for Q/A extraction and investigate task-specific retrieval models for answering questions. Our best model finds answers for 36% of the test questions in the top 20 results. Our overall conclusion is that FAQ pages on the web provide an excellent resource for addressing real users' information needs in a highly focused manner.
Starting Page	76
Ending Page	83
Page Count	8
File Format	PDF
ISBN	1595931406
DOI	10.1145/1099554.1099571
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2005-10-31
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Question answering Faq retrieval Questions beyond factoids
Content Type	Text
Resource Type	Article

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